1 Commits

Author SHA1 Message Date
9ddbb4a8e5 feat: wire real service agents into chat with LLM tool dispatch + Rivet proxy fix (#3)
# Wire All 4 Microservice Agents Into Chat

Wires all 4 microservice-backed agents into the chat so the LLM can call real services and return session URLs.

---

## Changes

### New

* `src/routes/chat.ts`

  * Added a direct HTTP chat endpoint.
  * When the LLM calls:

    * `start_interview_session`
    * `analyze_resume`
    * `start_roleplay_session`
    * `compute_qscore`
  * The route executes real service probes and returns live session URLs.

---

### Fixed

* `src/index.ts`

  * Rivet proxy now forwards requests to the engine at `localhost:6420`
    instead of using `registry.handler()`.
  * Prevents the:

    ```txt
    Runtime already started as runner
    ```

    conflict.

* `src/actors/user-actor.ts`

  * `receiveMessage()` now returns:

    ```ts
    {
      reply,
      sessions: []
    }
    ```
  * Includes per-module session URLs in responses.

* `docker-compose.yml`

  * Fixed:

    * Gitea health check port
    * Port mapping
    * `A2A_ALLOWED_KEY` default value

* `src/config.ts`

  * Added:

    ```ts
    resumeServiceUrl
    ```
  * Configured to use port `8002`.

---

### Rewritten

* `prompts/system.txt`

  * Reworked into a conversational step-by-step flow.
  * Added explicit rule:

    > CALL THE TOOL IMMEDIATELY

---

### Updated

* `agents/*.md` (6 files)

  * Updated:

    * Domain descriptions
    * Trigger phrases
    * Agent boundaries

---

## Verified

| Agent         | Service                  | Result                      |
| ------------- | ------------------------ | --------------------------- |
| Resume (Mira) | `resume-builder:8002`    | Real analysis               |
| Sara          | `interview-service:8007` | Real Gemini session + URL   |
| Emily         | `roleplay-service:8008`  | Real roleplay session + URL |
| Quinn         | `qscore-service:8000`    | Real Q-Score (~84)          |

---

## Outcome

The chat system can now:

* Trigger real backend agent services directly from LLM tool calls
* Return live session URLs
* Maintain structured multi-agent responses
* Avoid Rivet runtime conflicts
* Support end-to-end conversational workflows across all 4 agents

Reviewed-on: puter/growqr-backend#3
Co-authored-by: NinjasPyajamas <divyansh242805@gmail.com>
Co-committed-by: NinjasPyajamas <divyansh242805@gmail.com>
2026-06-01 09:26:19 +00:00